MINERVA

A dashboard from the MINERVA prototype. The MINERVA prototype consists of three tightly integrated components: a data base for scientific data products that also maintains analysis results, a 3D Visualization Engine and a non-spatial visualization component.

Figure 2: As part of the planned 3D GIS functionality, pins show measurement positions of different instruments in the 3D reconstruction of Cape Desire at the Victoria Crater. Blue ones indicate spectra and red ones radar data. A preview of one spectrum is shown as billboard. The yellow and green lines are part of a geologic interpretation. Data courtesy USGS/NASA/JPL/Caltech/ASU

Figure 3: Mockup of a dashboard for analyzing products. It combines information about the sample such as the location and the rover orientation, and it shows measured results such as spectra. The shown spectral data is courtesy of the USGS Spectral Database, all other views show simulation data which are courtesy of AVL List GmbH.

MINERVA: Mars Interactive Exploration based on Reconstruction and Visual Analysis. MINERVA is an integrated framework for planetary scientists allowing members of different instrument teams to cooperate synergistically in virtual workspaces by sharing observations, analyses and annotations of heterogonous mission data.

The ExoMars 2020 mission will provide a heterogeneous set of data from different instruments captured on the surface of Mars. It encompasses different types of imagery, various spectra, ground penetrating radar observations, and lab examinations of samples. The goal of MINERVA is to provide planetary scientists with an integrated framework that supports a comprehensive, holistic and efficient analysis of this wealth of heterogeneous science data. New interactive visualization methods considering semantics, meta-information and data modalities are investigated. The tight interoperation of a 3D explorer with GIS functionality and a visual analytics component will not merely make the analysis workflow more efficient but will allow insights, which would be hard or impossible to obtain using isolated methods.

Components

The MINERVA prototype will consist of three tightly integrated components:

Get geospatial overview of products’ locations having certain characteristics (e.g., a spectrum with a certain shape).

Simultaneous inspection of ensembles of spectra / images. This may include a characterization of the overall dispersion, a pairwise comparison of particular products, and the clustering of products by their characteristics (e.g., the shape of their spectrum).